Agentica Spawn

作者 parcadeid07ff4b06b62無授權條款3.9K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫8 個月前更新

Spawn Agentica multi-agent patterns

僅含說明AI & Agents

AI 產生的概覽

為任務啟動 Agentica 多代理模式，例如 Swarm、Hierarchical、Generator/Critic 與 Jury。

功能: 此技能會把選定的 Agentica 多代理模式對應到相應的啟動方法，並說明如何呼叫。內容涵蓋用於研究與探索的 Swarm、用於建置與實作的 Hierarchical、用於反覆精進的 Generator/Critic，以及用於驗證的 Jury。它也列出傳遞給所啟動代理的環境變數，例如 SWARM_ID、AGENT_ROLE 與 PATTERN_TYPE。
適用情境: 適用於 Agentica 協調器提示選擇模式之後，或使用者明確要求使用多代理模式時。它適合受益於平行代理的複雜任務，包括多觀點研究、協同實作、反覆精進或高風險驗證。
執行需求: 不隨附指令碼，僅為指示性內容。它假定存在具備所述模式類別的 Agentica 多代理執行環境，且環境會向所啟動的代理提供 SWARM_ID、AGENT_ROLE 與 PATTERN_TYPE。

Agentica Spawn Skill

Use this skill after user selects an Agentica pattern.

When to Use

After agentica-orchestrator prompts user for pattern selection
When user explicitly requests a multi-agent pattern (swarm, hierarchical, etc.)
When implementing complex tasks that benefit from parallel agent execution
For research tasks requiring multiple perspectives (use Swarm)
For implementation tasks requiring coordination (use Hierarchical)
For iterative refinement (use Generator/Critic)
For high-stakes validation (use Jury)

Pattern Selection to Spawn Method

Swarm (Research/Explore)

python

swarm = Swarm(    perspectives=[        "Security expert analyzing for vulnerabilities",        "Performance expert optimizing for speed",        "Architecture expert reviewing design"    ],    aggregate_mode=AggregateMode.MERGE,)result = await swarm.execute(task_description)

swarm = Swarm(    perspectives=[        "Security expert analyzing for vulnerabilities",        "Performance expert optimizing for speed",        "Architecture expert reviewing design"    ],    aggregate_mode=AggregateMode.MERGE,)result = await swarm.execute(task_description)

Hierarchical (Build/Implement)

python

hierarchical = Hierarchical(    coordinator_premise="You break tasks into subtasks",    specialist_premises={        "planner": "You create implementation plans",        "implementer": "You write code",        "reviewer": "You review code for issues"    },)result = await hierarchical.execute(task_description)

hierarchical = Hierarchical(    coordinator_premise="You break tasks into subtasks",    specialist_premises={        "planner": "You create implementation plans",        "implementer": "You write code",        "reviewer": "You review code for issues"    },)result = await hierarchical.execute(task_description)

Generator/Critic (Iterate/Refine)

python

gc = GeneratorCritic(    generator_premise="You generate solutions",    critic_premise="You critique and suggest improvements",    max_rounds=3,)result = await gc.run(task_description)

gc = GeneratorCritic(    generator_premise="You generate solutions",    critic_premise="You critique and suggest improvements",    max_rounds=3,)result = await gc.run(task_description)

Jury (Validate/Verify)

python

jury = Jury(    num_jurors=5,    consensus_mode=ConsensusMode.MAJORITY,    premise="You evaluate the solution")verdict = await jury.decide(bool, question)

jury = Jury(    num_jurors=5,    consensus_mode=ConsensusMode.MAJORITY,    premise="You evaluate the solution")verdict = await jury.decide(bool, question)

Environment Variables

All spawned agents receive:

SWARM_ID: Unique identifier for this swarm run
AGENT_ROLE: Role within the pattern (coordinator, specialist, etc.)
PATTERN_TYPE: Which pattern is running

來源與署名

來源：parcadei/continuous-claude-v3位於.claude/skills/agentica-spawn提交d07ff4b

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Agentica Spawn

Agentica Spawn Skill

When to Use

Pattern Selection to Spawn Method

Swarm (Research/Explore)

Hierarchical (Build/Implement)

Generator/Critic (Iterate/Refine)

Jury (Validate/Verify)

Environment Variables

來源與署名

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